A new method called QM-VM2 is presented that efficiently combines statistical mechanics with quantum mechanical (QM) energy potentials in order to calculate noncovalent binding free energies of host–guest systems. QM-VM2 efficiently couples the use of semi-empirical QM (SEQM) energies and geometry optimizations with an underlying molecular mechanics (MM) based conformational search, to find low SEQM energy minima, and allows for processing of these minima at higher levels of ab initio QM theory. A progressive geometry optimization scheme is introduced as a means to increase conformational sampling efficiency. The newly implemented QM-VM2 is used to compute the binding free energies of the host molecule cucurbit[7]uril and a set of 15 guest molecules. The results are presented along with comparisons to experimentally determined binding affinities. For the full set of 15 host–guest complexes, which have a range of formal charges from +1 to +3, SEQM-VM2 based binding free energies show poor correlation with experiment, whereas for the ten +1 complexes only, a significant correlation (R2 = 0.8) is achieved. SEQM-VM2 generation of conformers followed by single-point ab initio QM calculations at the dispersion corrected restricted Hartree–Fock-D3(BJ) and TPSS-D3(BJ) levels of theory, as post-processing corrections, yields a reasonable correlation with experiment for the full set of host–guest complexes (R2 = 0.6 and R2 = 0.7, respectively) and an excellent correlation for the +1 formal charge set (R2 = 1.0 and R2 = 0.9, respectively), as long as a sufficiently large basis set (triple-zeta quality) is employed. The importance of the inclusion of configurational entropy, even at the MM level, for the achievement of good correlation with experiment was demonstrated by comparing the calculated ΔE values with experiment and finding a considerably poorer correlation with experiment than for the calculated free energy ΔE − TΔS. For the complete set of host–guest systems with the range of formal charges, it was observed that the deviation of the predicted binding free energy from experiment correlates somewhat with the net charge of the systems. This observation leads to a simple empirical interpolation scheme to improve the linear regression of the full set.
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14 March 2021
Research Article|
March 12 2021
Computation of host–guest binding free energies with a new quantum mechanics based mining minima algorithm
Special Collection:
Special Collection in Honor of Women in Chemical Physics and Physical Chemistry
Peng Xu
;
Peng Xu
1
Department of Chemistry, Iowa State University
, Ames, Iowa 50014, USA
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Tosaporn Sattasathuchana
;
Tosaporn Sattasathuchana
1
Department of Chemistry, Iowa State University
, Ames, Iowa 50014, USA
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Emilie Guidez
;
Emilie Guidez
2
Department of Chemistry, University of Colorado Denver
, Denver, Colorado 80204, USA
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Simon P. Webb
;
Simon P. Webb
3
VeraChem LLC
, 12850 Middlebrook Rd. Ste 205, Germantown, Maryland 20874-5244, USA
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Kilinoelani Montgomery;
Kilinoelani Montgomery
2
Department of Chemistry, University of Colorado Denver
, Denver, Colorado 80204, USA
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Hussna Yasini;
Hussna Yasini
2
Department of Chemistry, University of Colorado Denver
, Denver, Colorado 80204, USA
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Iara F. M. Pedreira;
Iara F. M. Pedreira
2
Department of Chemistry, University of Colorado Denver
, Denver, Colorado 80204, USA
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Mark S. Gordon
Mark S. Gordon
a)
1
Department of Chemistry, Iowa State University
, Ames, Iowa 50014, USA
a)Author to whom correspondence should be addressed: mark@si.msg.chem.iastate.edu
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a)Author to whom correspondence should be addressed: mark@si.msg.chem.iastate.edu
Note: This paper is part of the JCP Special Collection in Honor of Women in Chemical Physics and Physical Chemistry.
J. Chem. Phys. 154, 104122 (2021)
Article history
Received:
December 15 2020
Accepted:
February 11 2021
Citation
Peng Xu, Tosaporn Sattasathuchana, Emilie Guidez, Simon P. Webb, Kilinoelani Montgomery, Hussna Yasini, Iara F. M. Pedreira, Mark S. Gordon; Computation of host–guest binding free energies with a new quantum mechanics based mining minima algorithm. J. Chem. Phys. 14 March 2021; 154 (10): 104122. https://doi.org/10.1063/5.0040759
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